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Analysis of berberine and total alkaloid content in Cortex Phellodendri by near infrared spectroscopy (NIRS) compared with high-performance liquid chromatography coupled with ultra-visible spectrometric detection

机译:近红外光谱(NIRS)与高效液相色谱结合超可见光谱检测相比较,分析黄柏中的小ber碱和总生物碱含量

摘要

This paper developed a rapid method using near infrared spectroscopy (NIRS) to differentiate two species of Cortex Phellodendri (CP), Cortex Phellodendri Chinensis (PCS) and Cortex Phellodendri Amurensis (PAR), and to predict quantitatively the content of berberine and total alkaloid content in all Cortex Phellodendri samples. Three alkaloids, berberine, jatrorrhizine and palmatine were analyzed simultaneously with a Thermo ODS Hypersil column by gradient elution with a new mobile phase under high-performance liquid chromatography-diode array detection (HPLC-DAD). Berberine content determined by HPLC-DAD was exploited as a critical parameter for successful discrimination between them. Multiplicative scatter correction (MSC), second derivative and Savitsky-Golay (S.G.) were utilized together to correct the scattering effect and eliminate the baseline shift in all near infrared diffuse reflectance spectra as well as to enhance spectral features in order to give a better correlation with the results obtained by HPLC-DAD. With the use of principal component analysis (PCA), samples datasets were separated successfully into two different clusters corresponding to two species. Furthermore, a partial least squares (PLS) regression method was built on the correlation model. The results showed that the correlation coefficients of the prediction models were R = 0.996 for the berberine and R = 0.994 for total alkaloid content. The influences of water absorption bands present in the NIR spectra on the models were also investigated in order to explore the practicability of NIRS in routine use. The outcome showed that NIRS possibly acts as routine screening in the quality control of Chinese herbal medicine.
机译:本文开发了一种使用近红外光谱(NIRS)区分皮草黄柏(CP),黄柏(PCS)和黄柏(PAR)的快速方法,并定量预测了小ber碱含量和总生物碱含量在所有Cortex Phellodendri样品中。在高效液相色谱-二极管阵列检测(HPLC-DAD)下,用新型流动相通过Thermo ODS Hypersil色谱柱同时洗脱三种生物碱,小ber碱,麻疯子碱和棕榈碱。通过HPLC-DAD测定的小ber碱含量被用作成功区分它们的关键参数。乘法散射校正(MSC),二阶导数和Savitsky-Golay(SG)一起用于校正散射效应并消除所有近红外漫反射光谱中的基线偏移,并增强光谱特征以提供更好的相关性通过HPLC-DAD获得的结果。通过使用主成分分析(PCA),成功地将样品数据集分为两个不同的簇,分别对应两个物种。此外,在相关模型上建立了偏最小二乘(PLS)回归方法。结果表明,黄连素的预测模型的相关系数为R = 0.996,总生物碱含量的相关系数为R = 0.994。还研究了近红外光谱中存在的吸水带对模型的影响,以探索NIRS在常规使用中的实用性。结果表明,NIRS可以作为中药质量控制中的常规检查。

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